SIMULATION OF AN IOT AIR QUALITY MONITORING SYSTEM

Air pollution remains a major global health and environmental concern, driving the need for efficient and scalable monitoring systems. This paper presents a simulationbased Internet of Things architecture for air quality monitoring, focusing on real-time data transmission, anomaly detection, and visual analysis. The system simulates 25 monitoring stations, each with six virtual sensors representing key pollutants, totaling 150 sensor processes. These sensors communicate with dedicated gateway processes via MQTT and transmit data to a cloud-hosted web server for aggregation, air quality index calculation, visualization, and database storage. The simulation uses real-world data collected in Seoul to emulate realistic pollution conditions. An interactive web interface displays live air quality index values through maps and time series charts, allowing the detection of anomalies.